A technique for detecting a target object located near a vehicle, calculating a distance between the target object and the vehicle based on image data captured by a camera mounted on the vehicle, and controlling a movement of the vehicle in such a manner that the vehicle does not collide with the target object has been requested. In addition, it is preferable that a monocular camera be used due to a camera cost limitation, a mounting position limitation, and the like.
For example, as conventional techniques for detecting a target object from image data captured by a monocular camera, there are machine learning and optical flow. In addition, as conventional techniques for calculating a distance between a target object and a vehicle, there are a motion stereo method and a contact position determination method.
For example, in the machine learning, deep learning and characteristic amounts of histograms of oriented gradients (HoG) are used in some cases. The machine learning collects image data of a detected target object in advance, calculates characteristic amounts of the target object, and causes the calculated characteristic amounts to be held as classifiers. The machine learning compares the image data with the classifiers, executes matching to determine whether or not the image data includes a characteristic amount matching a characteristic amount included in the classifiers, and detects the target object included in the image data.
The optical flow detects characteristic points from image data and identifies a target object based on variations in coordinates of the characteristic points.
The motion stereo method measures a distance from a vehicle to a target object based on the amount of a movement of the vehicle and image data before and after the movement of the vehicle. In the motion stereo method, a movement amount of a vehicle may be accurately identified, and if a target object does not move, a distance between the vehicle and the target object may be measured with high accuracy.
The contact position determination method uses the machine learning or the optical flow to detect a target object from image data at a preliminary stage and geometrically calculates a distance between the target object and a vehicle based on coordinates of the detected target object on an image and a distortion table.
Examples of related art are Japanese Laid-open Patent Publication No. 2010-211578 and International Publication Pamphlet No. WO2008/065729.